Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it returns a 'full write-up', implying a read operation, but does not explicitly label it as read-only or mention any potential side effects, error conditions, or authentication requirements. For a simple getter this is acceptable, but it leaves some ambiguity about failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two short sentences that immediately convey the purpose and the required input. Every word adds value, and it is front-loaded with the core action. No redundancy or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (one parameter, no output schema, no annotations), the description adequately covers what the tool does and how to invoke it. It explains the return type ('full write-up') and the source of the slug. It does not mention error handling or return format, but those are not critical for an agent's decision to use this tool. Slight room for improvement by noting it is read-only, but overall sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The parameter slug is fully described in the input schema with a clear example. The tool description reinforces that the slug comes from list_case_studies, which adds context beyond the schema. Since schema coverage is 100%, the baseline is 3, and the description does not need to elaborate further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves the full write-up for a single case study, using a specific verb ('get') and resource ('case study'). It explicitly distinguishes itself from list_case_studies by mentioning the slug comes from that list, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear prerequisite: a slug returned by list_case_studies. This implies the sequence (list first, then get), which is valuable guidance. However, it does not explicitly contrast this tool with alternatives beyond the implicit mention of list_case_studies, nor does it state when NOT to use it, so it stops short of full explicitness.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so description carries the full burden. It lists the contents of the response but does not explicitly disclose behavioral aspects such as read-only nature, potential side effects, or any constraints. Since it's a simple retrieval, this is adequate but not enriching.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with 'What GingerLive is:', then a clear list of content. No waste, perfectly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all necessary information for a tool with no inputs and no output schema. It adequately explains what the user gets, and given the low complexity, it is complete enough for selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters and 100% schema description coverage (vacuously), the description does not need to explain any parameters. Baseline for 0 params is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states what the tool does: provides a company overview with specific elements (positioning, platforms, stats, partners, links). It is specific and distinct from siblings like get_network_stats, which focuses only on stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context on what the tool returns (overview content), making usage obvious. However, it doesn't explicitly mention when to prefer alternatives like get_network_stats for detailed stats, so it lacks explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral transparency. It accurately discloses that this is a read-only reporting tool providing specific metrics. However, it does not explicitly state read-only semantics, whether it requires authorization, or clarify time periods/units for the statistics. Adequate but not extensive coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the subject ('GingerLive's network reach and performance numbers') and uses a colon to introduce a concise list of specific metrics. No wasted words; every element earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity—zero parameters and no output schema—the description covers the key data points a caller would need (the exact metrics returned). Unit/timeframe details would be helpful but aren't critical given the straightforward nature of the aggregate numbers listed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, so the schema provides no actionable information, warranting a baseline of 4 per the rubric. The description advantageously lists the exact metrics returned (streamer count, reach, hours, view-through rate), which adds context beyond what the empty schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the subject ('GingerLive's network reach and performance numbers') and lists four specific metrics (streamer count, annual unique reach, hours watched, ad view-through rate). This level of specificity makes the tool's purpose immediately apparent and distinguishes it from siblings like get_company_overview or list_case_studies which address different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit when-to-use or when-not-to-use guidance, and no alternatives are named. However, the tool name and description make its purpose obvious, so usage is implied rather than stated. This falls short of a 4 because there's no clear context about when to prefer it over adjacent tools like get_company_overview.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations supplied, the description carries the full behavioral burden, yet it only describes topical content rather than behavioral traits (e.g., no mention of data freshness, access requirements, or cost-accuracy caveats). That said, nothing is misleading and the read-style nature is apparent from the content framing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single ~22-word sentence that front-loads the subject and uses a colon-delimited list for scanability. Nearly every word earns its place, though 'how it works' slightly echoes the opening clause 'How a streamer joins and monetizes'.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, parameterless informational tool, the description is thorough: it covers cost, mechanics, supported platforms, and the sign-up link. Additional caveats like information freshness or geographic availability could help but are non-critical for this low-complexity use case.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters and vacuously 100% schema coverage, the baseline 4 applies. The description doesn't need to explain parameter semantics since no inputs exist, and it doesn't add any misleading parameter information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource (GingerLive streamer program) and itemizes the informational scope ('cost, how it works, supported platforms, and the sign-up link'). It's distinct from siblings like get_company_overview and list_ad_formats by subject matter, though it never explicitly differentiates itself or uses a crisp imperative verb.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is provided. The description gives zero context for choosing this tool over get_company_overview or get_network_stats, and no exclusions or alternatives are named. The agent must rely on the tool name alone to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries the burden. It states the output includes descriptions and badges, but does not explicitly mention that it is a safe read-only operation or address any side effects. For a simple list tool, this is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that directly states the tool's purpose and output. Every word contributes value, and it is not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with no parameters and no output schema, the description provides the key details: it returns formats with descriptions and badges, with an example badge. It is complete enough for the agent to understand the output without further elaboration.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, and the schema has no properties. The description adds no parameter details because none exist, but it clearly explains what the output will contain, which is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists livestream ad formats offered to brands, including descriptions and badges. It distinguishes from siblings by focusing on ad formats, not case studies or network stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: to retrieve a list of ad formats. It does not explicitly say when to use this tool versus alternatives, but the sibling tools are clearly different in purpose. No exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It states the item format (excerpt and link) and points to detail retrieval, but it does not mention return container/pagination, sorting, or access constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One compact sentence front-loads the verb and resource, immediately identifies output contents, and adds a pointer to the sibling detail tool. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity, zero-parameter list tool, the description covers purpose, item structure, and how to get more detail. It doesn't mention whether the list is complete/paginated or sort order, but this is a minor gap given no output schema and simple semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema has 100% coverage, so the baseline of 4 applies. There are no parameter meanings to clarify, and the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource ('List case studies') and clearly distinguishes from sibling get_case_study by noting each item includes an excerpt and link. This identifies the tool's purpose and scope unambiguously.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly tells the agent to call get_case_study with a slug for the full write-up, thereby setting when to use this list vs the detail sibling. This is an explicit alternative/usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.